{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "pixar_movies = pd.read_csv(\"PixarMovies.csv\")\n",
    "# Number of rows\n",
    "print(pixar_movies.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16\n"
     ]
    }
   ],
   "source": [
    "# Number of columns\n",
    "print(pixar_movies.shape[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year Released</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Length</th>\n",
       "      <th>RT Score</th>\n",
       "      <th>IMDB Score</th>\n",
       "      <th>Metacritic Score</th>\n",
       "      <th>Opening Weekend</th>\n",
       "      <th>Worldwide Gross</th>\n",
       "      <th>Domestic Gross</th>\n",
       "      <th>Adjusted Domestic Gross</th>\n",
       "      <th>International Gross</th>\n",
       "      <th>Domestic %</th>\n",
       "      <th>International %</th>\n",
       "      <th>Production Budget</th>\n",
       "      <th>Oscars Nominated</th>\n",
       "      <th>Oscars Won</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0 </th>\n",
       "      <td> 1995</td>\n",
       "      <td>           Toy Story</td>\n",
       "      <td>  81</td>\n",
       "      <td> 100</td>\n",
       "      <td> 8.3</td>\n",
       "      <td> 92</td>\n",
       "      <td>  29.14</td>\n",
       "      <td>  362.0</td>\n",
       "      <td> 191.8</td>\n",
       "      <td> 356.21</td>\n",
       "      <td> 170.2</td>\n",
       "      <td> 52.98%</td>\n",
       "      <td> 47.02%</td>\n",
       "      <td>  30</td>\n",
       "      <td>  3</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1 </th>\n",
       "      <td> 1998</td>\n",
       "      <td>        A Bug's Life</td>\n",
       "      <td>  96</td>\n",
       "      <td>  92</td>\n",
       "      <td> 7.2</td>\n",
       "      <td> 77</td>\n",
       "      <td>  33.26</td>\n",
       "      <td>  363.4</td>\n",
       "      <td> 162.8</td>\n",
       "      <td> 277.18</td>\n",
       "      <td> 200.6</td>\n",
       "      <td> 44.80%</td>\n",
       "      <td> 55.20%</td>\n",
       "      <td>  45</td>\n",
       "      <td>  1</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2 </th>\n",
       "      <td> 1999</td>\n",
       "      <td>         Toy Story 2</td>\n",
       "      <td>  92</td>\n",
       "      <td> 100</td>\n",
       "      <td> 7.9</td>\n",
       "      <td> 88</td>\n",
       "      <td>  57.39</td>\n",
       "      <td>  485.0</td>\n",
       "      <td> 245.9</td>\n",
       "      <td> 388.43</td>\n",
       "      <td> 239.2</td>\n",
       "      <td> 50.70%</td>\n",
       "      <td> 49.32%</td>\n",
       "      <td>  90</td>\n",
       "      <td>  1</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3 </th>\n",
       "      <td> 2001</td>\n",
       "      <td>      Monsters, Inc.</td>\n",
       "      <td>  90</td>\n",
       "      <td>  96</td>\n",
       "      <td> 8.1</td>\n",
       "      <td> 78</td>\n",
       "      <td>  62.58</td>\n",
       "      <td>  528.8</td>\n",
       "      <td> 255.9</td>\n",
       "      <td> 366.12</td>\n",
       "      <td> 272.9</td>\n",
       "      <td> 48.39%</td>\n",
       "      <td> 51.61%</td>\n",
       "      <td> 115</td>\n",
       "      <td>  3</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4 </th>\n",
       "      <td> 2003</td>\n",
       "      <td>        Finding Nemo</td>\n",
       "      <td> 104</td>\n",
       "      <td>  99</td>\n",
       "      <td> 8.2</td>\n",
       "      <td> 90</td>\n",
       "      <td>  70.25</td>\n",
       "      <td>  895.6</td>\n",
       "      <td> 339.7</td>\n",
       "      <td> 457.46</td>\n",
       "      <td> 555.9</td>\n",
       "      <td> 37.93%</td>\n",
       "      <td> 62.07%</td>\n",
       "      <td>  94</td>\n",
       "      <td>  4</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5 </th>\n",
       "      <td> 2004</td>\n",
       "      <td>     The Incredibles</td>\n",
       "      <td> 115</td>\n",
       "      <td>  97</td>\n",
       "      <td> 8.0</td>\n",
       "      <td> 90</td>\n",
       "      <td>  70.47</td>\n",
       "      <td>  631.4</td>\n",
       "      <td> 261.4</td>\n",
       "      <td> 341.28</td>\n",
       "      <td> 370.0</td>\n",
       "      <td> 41.40%</td>\n",
       "      <td> 58.60%</td>\n",
       "      <td>  92</td>\n",
       "      <td>  4</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6 </th>\n",
       "      <td> 2006</td>\n",
       "      <td>                Cars</td>\n",
       "      <td> 116</td>\n",
       "      <td>  74</td>\n",
       "      <td> 7.2</td>\n",
       "      <td> 73</td>\n",
       "      <td>  60.12</td>\n",
       "      <td>  462.0</td>\n",
       "      <td> 244.1</td>\n",
       "      <td> 302.59</td>\n",
       "      <td> 217.9</td>\n",
       "      <td> 52.84%</td>\n",
       "      <td> 47.16%</td>\n",
       "      <td>  70</td>\n",
       "      <td>  2</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7 </th>\n",
       "      <td> 2007</td>\n",
       "      <td>         Ratatouille</td>\n",
       "      <td> 111</td>\n",
       "      <td>  96</td>\n",
       "      <td> 8.0</td>\n",
       "      <td> 96</td>\n",
       "      <td>  47.00</td>\n",
       "      <td>  623.7</td>\n",
       "      <td> 206.4</td>\n",
       "      <td> 243.65</td>\n",
       "      <td> 417.3</td>\n",
       "      <td> 33.09%</td>\n",
       "      <td> 66.91%</td>\n",
       "      <td> 150</td>\n",
       "      <td>  5</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8 </th>\n",
       "      <td> 2008</td>\n",
       "      <td>              WALL-E</td>\n",
       "      <td>  97</td>\n",
       "      <td>  96</td>\n",
       "      <td> 8.4</td>\n",
       "      <td> 94</td>\n",
       "      <td>  63.10</td>\n",
       "      <td>  521.3</td>\n",
       "      <td> 223.8</td>\n",
       "      <td> 253.11</td>\n",
       "      <td> 297.5</td>\n",
       "      <td> 42.93%</td>\n",
       "      <td> 57.07%</td>\n",
       "      <td> 180</td>\n",
       "      <td>  6</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9 </th>\n",
       "      <td> 2009</td>\n",
       "      <td>                  Up</td>\n",
       "      <td>  96</td>\n",
       "      <td>  98</td>\n",
       "      <td> 8.3</td>\n",
       "      <td> 88</td>\n",
       "      <td>  68.11</td>\n",
       "      <td>  731.3</td>\n",
       "      <td> 293.0</td>\n",
       "      <td> 318.90</td>\n",
       "      <td> 438.3</td>\n",
       "      <td> 40.07%</td>\n",
       "      <td> 59.93%</td>\n",
       "      <td> 175</td>\n",
       "      <td>  5</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td> 2010</td>\n",
       "      <td>         Toy Story 3</td>\n",
       "      <td> 103</td>\n",
       "      <td>  99</td>\n",
       "      <td> 8.4</td>\n",
       "      <td> 92</td>\n",
       "      <td> 110.31</td>\n",
       "      <td> 1063.2</td>\n",
       "      <td> 415.0</td>\n",
       "      <td> 423.88</td>\n",
       "      <td> 648.2</td>\n",
       "      <td> 39.03%</td>\n",
       "      <td> 60.97%</td>\n",
       "      <td> 200</td>\n",
       "      <td>  5</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td> 2011</td>\n",
       "      <td>              Cars 2</td>\n",
       "      <td> 113</td>\n",
       "      <td>  39</td>\n",
       "      <td> 6.3</td>\n",
       "      <td> 57</td>\n",
       "      <td> 109.00</td>\n",
       "      <td>  559.9</td>\n",
       "      <td> 191.5</td>\n",
       "      <td> 194.43</td>\n",
       "      <td> 368.4</td>\n",
       "      <td> 34.20%</td>\n",
       "      <td> 65.80%</td>\n",
       "      <td> 200</td>\n",
       "      <td>  0</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td> 2012</td>\n",
       "      <td>               Brave</td>\n",
       "      <td> 100</td>\n",
       "      <td>  78</td>\n",
       "      <td> 7.2</td>\n",
       "      <td> 69</td>\n",
       "      <td>  66.30</td>\n",
       "      <td>  539.0</td>\n",
       "      <td> 237.3</td>\n",
       "      <td> 243.39</td>\n",
       "      <td> 301.7</td>\n",
       "      <td> 44.03%</td>\n",
       "      <td> 55.97%</td>\n",
       "      <td> 185</td>\n",
       "      <td>  1</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td> 2013</td>\n",
       "      <td> Monsters University</td>\n",
       "      <td> 107</td>\n",
       "      <td>  78</td>\n",
       "      <td> 7.4</td>\n",
       "      <td> 65</td>\n",
       "      <td>  82.43</td>\n",
       "      <td>  743.6</td>\n",
       "      <td> 268.5</td>\n",
       "      <td> 269.59</td>\n",
       "      <td> 475.1</td>\n",
       "      <td> 36.11%</td>\n",
       "      <td> 63.89%</td>\n",
       "      <td> 200</td>\n",
       "      <td>  0</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td> 2015</td>\n",
       "      <td>          Inside Out</td>\n",
       "      <td> 102</td>\n",
       "      <td>  98</td>\n",
       "      <td> 8.8</td>\n",
       "      <td> 93</td>\n",
       "      <td>  90.40</td>\n",
       "      <td>  677.1</td>\n",
       "      <td> 340.5</td>\n",
       "      <td> 340.50</td>\n",
       "      <td> 336.6</td>\n",
       "      <td> 50.29%</td>\n",
       "      <td> 49.71%</td>\n",
       "      <td> 175</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year Released                Movie  Length  RT Score  IMDB Score  \\\n",
       "0            1995            Toy Story      81       100         8.3   \n",
       "1            1998         A Bug's Life      96        92         7.2   \n",
       "2            1999          Toy Story 2      92       100         7.9   \n",
       "3            2001       Monsters, Inc.      90        96         8.1   \n",
       "4            2003         Finding Nemo     104        99         8.2   \n",
       "5            2004      The Incredibles     115        97         8.0   \n",
       "6            2006                 Cars     116        74         7.2   \n",
       "7            2007          Ratatouille     111        96         8.0   \n",
       "8            2008               WALL-E      97        96         8.4   \n",
       "9            2009                   Up      96        98         8.3   \n",
       "10           2010          Toy Story 3     103        99         8.4   \n",
       "11           2011               Cars 2     113        39         6.3   \n",
       "12           2012                Brave     100        78         7.2   \n",
       "13           2013  Monsters University     107        78         7.4   \n",
       "14           2015           Inside Out     102        98         8.8   \n",
       "\n",
       "    Metacritic Score  Opening Weekend  Worldwide Gross  Domestic Gross  \\\n",
       "0                 92            29.14            362.0           191.8   \n",
       "1                 77            33.26            363.4           162.8   \n",
       "2                 88            57.39            485.0           245.9   \n",
       "3                 78            62.58            528.8           255.9   \n",
       "4                 90            70.25            895.6           339.7   \n",
       "5                 90            70.47            631.4           261.4   \n",
       "6                 73            60.12            462.0           244.1   \n",
       "7                 96            47.00            623.7           206.4   \n",
       "8                 94            63.10            521.3           223.8   \n",
       "9                 88            68.11            731.3           293.0   \n",
       "10                92           110.31           1063.2           415.0   \n",
       "11                57           109.00            559.9           191.5   \n",
       "12                69            66.30            539.0           237.3   \n",
       "13                65            82.43            743.6           268.5   \n",
       "14                93            90.40            677.1           340.5   \n",
       "\n",
       "    Adjusted Domestic Gross  International Gross Domestic % International %  \\\n",
       "0                    356.21                170.2     52.98%          47.02%   \n",
       "1                    277.18                200.6     44.80%          55.20%   \n",
       "2                    388.43                239.2     50.70%          49.32%   \n",
       "3                    366.12                272.9     48.39%          51.61%   \n",
       "4                    457.46                555.9     37.93%          62.07%   \n",
       "5                    341.28                370.0     41.40%          58.60%   \n",
       "6                    302.59                217.9     52.84%          47.16%   \n",
       "7                    243.65                417.3     33.09%          66.91%   \n",
       "8                    253.11                297.5     42.93%          57.07%   \n",
       "9                    318.90                438.3     40.07%          59.93%   \n",
       "10                   423.88                648.2     39.03%          60.97%   \n",
       "11                   194.43                368.4     34.20%          65.80%   \n",
       "12                   243.39                301.7     44.03%          55.97%   \n",
       "13                   269.59                475.1     36.11%          63.89%   \n",
       "14                   340.50                336.6     50.29%          49.71%   \n",
       "\n",
       "    Production Budget  Oscars Nominated  Oscars Won  \n",
       "0                  30                 3           0  \n",
       "1                  45                 1           0  \n",
       "2                  90                 1           0  \n",
       "3                 115                 3           1  \n",
       "4                  94                 4           1  \n",
       "5                  92                 4           2  \n",
       "6                  70                 2           0  \n",
       "7                 150                 5           1  \n",
       "8                 180                 6           1  \n",
       "9                 175                 5           2  \n",
       "10                200                 5           2  \n",
       "11                200                 0           0  \n",
       "12                185                 1           1  \n",
       "13                200                 0           0  \n",
       "14                175               NaN         NaN  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pixar_movies.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year Released                int64\n",
       "Movie                       object\n",
       "Length                       int64\n",
       "RT Score                     int64\n",
       "IMDB Score                 float64\n",
       "Metacritic Score             int64\n",
       "Opening Weekend            float64\n",
       "Worldwide Gross            float64\n",
       "Domestic Gross             float64\n",
       "Adjusted Domestic Gross    float64\n",
       "International Gross        float64\n",
       "Domestic %                  object\n",
       "International %             object\n",
       "Production Budget            int64\n",
       "Oscars Nominated           float64\n",
       "Oscars Won                 float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pixar_movies.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Use the `str` attribute followed by the string method `rstrip()` to apply the string method \n",
    "# to every value in the column.  Use the `astype()` method to cast the column to the float data type.\n",
    "pixar_movies[\"Domestic %\"] = pixar_movies[\"Domestic %\"].str.rstrip(\"%\").astype(\"float\")\n",
    "pixar_movies[\"International %\"] = pixar_movies[\"International %\"].str.rstrip(\"%\").astype(\"float\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Multiply the `IMDB Score` column by 10\n",
    "pixar_movies[\"IMDB Score\"] = pixar_movies[\"IMDB Score\"]*10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Create a new DataFrame containing only the first 14 rows.\n",
    "filtered_pixar = pixar_movies.loc[0:13]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set the `Movie` column as the index for the DataFrame.\n",
    "pixar_movies.set_index(\"Movie\", inplace=True)\n",
    "filtered_pixar.set_index(\"Movie\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year Released</th>\n",
       "      <th>Length</th>\n",
       "      <th>RT Score</th>\n",
       "      <th>IMDB Score</th>\n",
       "      <th>Metacritic Score</th>\n",
       "      <th>Opening Weekend</th>\n",
       "      <th>Worldwide Gross</th>\n",
       "      <th>Domestic Gross</th>\n",
       "      <th>Adjusted Domestic Gross</th>\n",
       "      <th>International Gross</th>\n",
       "      <th>Domestic %</th>\n",
       "      <th>International %</th>\n",
       "      <th>Production Budget</th>\n",
       "      <th>Oscars Nominated</th>\n",
       "      <th>Oscars Won</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Movie</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Toy Story</th>\n",
       "      <td> 1995</td>\n",
       "      <td>  81</td>\n",
       "      <td> 100</td>\n",
       "      <td> 83</td>\n",
       "      <td> 92</td>\n",
       "      <td>  29.14</td>\n",
       "      <td>  362.0</td>\n",
       "      <td> 191.8</td>\n",
       "      <td> 356.21</td>\n",
       "      <td> 170.2</td>\n",
       "      <td> 52.98</td>\n",
       "      <td> 47.02</td>\n",
       "      <td>  30</td>\n",
       "      <td>  3</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Bug's Life</th>\n",
       "      <td> 1998</td>\n",
       "      <td>  96</td>\n",
       "      <td>  92</td>\n",
       "      <td> 72</td>\n",
       "      <td> 77</td>\n",
       "      <td>  33.26</td>\n",
       "      <td>  363.4</td>\n",
       "      <td> 162.8</td>\n",
       "      <td> 277.18</td>\n",
       "      <td> 200.6</td>\n",
       "      <td> 44.80</td>\n",
       "      <td> 55.20</td>\n",
       "      <td>  45</td>\n",
       "      <td>  1</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toy Story 2</th>\n",
       "      <td> 1999</td>\n",
       "      <td>  92</td>\n",
       "      <td> 100</td>\n",
       "      <td> 79</td>\n",
       "      <td> 88</td>\n",
       "      <td>  57.39</td>\n",
       "      <td>  485.0</td>\n",
       "      <td> 245.9</td>\n",
       "      <td> 388.43</td>\n",
       "      <td> 239.2</td>\n",
       "      <td> 50.70</td>\n",
       "      <td> 49.32</td>\n",
       "      <td>  90</td>\n",
       "      <td>  1</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monsters, Inc.</th>\n",
       "      <td> 2001</td>\n",
       "      <td>  90</td>\n",
       "      <td>  96</td>\n",
       "      <td> 81</td>\n",
       "      <td> 78</td>\n",
       "      <td>  62.58</td>\n",
       "      <td>  528.8</td>\n",
       "      <td> 255.9</td>\n",
       "      <td> 366.12</td>\n",
       "      <td> 272.9</td>\n",
       "      <td> 48.39</td>\n",
       "      <td> 51.61</td>\n",
       "      <td> 115</td>\n",
       "      <td>  3</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finding Nemo</th>\n",
       "      <td> 2003</td>\n",
       "      <td> 104</td>\n",
       "      <td>  99</td>\n",
       "      <td> 82</td>\n",
       "      <td> 90</td>\n",
       "      <td>  70.25</td>\n",
       "      <td>  895.6</td>\n",
       "      <td> 339.7</td>\n",
       "      <td> 457.46</td>\n",
       "      <td> 555.9</td>\n",
       "      <td> 37.93</td>\n",
       "      <td> 62.07</td>\n",
       "      <td>  94</td>\n",
       "      <td>  4</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Incredibles</th>\n",
       "      <td> 2004</td>\n",
       "      <td> 115</td>\n",
       "      <td>  97</td>\n",
       "      <td> 80</td>\n",
       "      <td> 90</td>\n",
       "      <td>  70.47</td>\n",
       "      <td>  631.4</td>\n",
       "      <td> 261.4</td>\n",
       "      <td> 341.28</td>\n",
       "      <td> 370.0</td>\n",
       "      <td> 41.40</td>\n",
       "      <td> 58.60</td>\n",
       "      <td>  92</td>\n",
       "      <td>  4</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cars</th>\n",
       "      <td> 2006</td>\n",
       "      <td> 116</td>\n",
       "      <td>  74</td>\n",
       "      <td> 72</td>\n",
       "      <td> 73</td>\n",
       "      <td>  60.12</td>\n",
       "      <td>  462.0</td>\n",
       "      <td> 244.1</td>\n",
       "      <td> 302.59</td>\n",
       "      <td> 217.9</td>\n",
       "      <td> 52.84</td>\n",
       "      <td> 47.16</td>\n",
       "      <td>  70</td>\n",
       "      <td>  2</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ratatouille</th>\n",
       "      <td> 2007</td>\n",
       "      <td> 111</td>\n",
       "      <td>  96</td>\n",
       "      <td> 80</td>\n",
       "      <td> 96</td>\n",
       "      <td>  47.00</td>\n",
       "      <td>  623.7</td>\n",
       "      <td> 206.4</td>\n",
       "      <td> 243.65</td>\n",
       "      <td> 417.3</td>\n",
       "      <td> 33.09</td>\n",
       "      <td> 66.91</td>\n",
       "      <td> 150</td>\n",
       "      <td>  5</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WALL-E</th>\n",
       "      <td> 2008</td>\n",
       "      <td>  97</td>\n",
       "      <td>  96</td>\n",
       "      <td> 84</td>\n",
       "      <td> 94</td>\n",
       "      <td>  63.10</td>\n",
       "      <td>  521.3</td>\n",
       "      <td> 223.8</td>\n",
       "      <td> 253.11</td>\n",
       "      <td> 297.5</td>\n",
       "      <td> 42.93</td>\n",
       "      <td> 57.07</td>\n",
       "      <td> 180</td>\n",
       "      <td>  6</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Up</th>\n",
       "      <td> 2009</td>\n",
       "      <td>  96</td>\n",
       "      <td>  98</td>\n",
       "      <td> 83</td>\n",
       "      <td> 88</td>\n",
       "      <td>  68.11</td>\n",
       "      <td>  731.3</td>\n",
       "      <td> 293.0</td>\n",
       "      <td> 318.90</td>\n",
       "      <td> 438.3</td>\n",
       "      <td> 40.07</td>\n",
       "      <td> 59.93</td>\n",
       "      <td> 175</td>\n",
       "      <td>  5</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toy Story 3</th>\n",
       "      <td> 2010</td>\n",
       "      <td> 103</td>\n",
       "      <td>  99</td>\n",
       "      <td> 84</td>\n",
       "      <td> 92</td>\n",
       "      <td> 110.31</td>\n",
       "      <td> 1063.2</td>\n",
       "      <td> 415.0</td>\n",
       "      <td> 423.88</td>\n",
       "      <td> 648.2</td>\n",
       "      <td> 39.03</td>\n",
       "      <td> 60.97</td>\n",
       "      <td> 200</td>\n",
       "      <td>  5</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cars 2</th>\n",
       "      <td> 2011</td>\n",
       "      <td> 113</td>\n",
       "      <td>  39</td>\n",
       "      <td> 63</td>\n",
       "      <td> 57</td>\n",
       "      <td> 109.00</td>\n",
       "      <td>  559.9</td>\n",
       "      <td> 191.5</td>\n",
       "      <td> 194.43</td>\n",
       "      <td> 368.4</td>\n",
       "      <td> 34.20</td>\n",
       "      <td> 65.80</td>\n",
       "      <td> 200</td>\n",
       "      <td>  0</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brave</th>\n",
       "      <td> 2012</td>\n",
       "      <td> 100</td>\n",
       "      <td>  78</td>\n",
       "      <td> 72</td>\n",
       "      <td> 69</td>\n",
       "      <td>  66.30</td>\n",
       "      <td>  539.0</td>\n",
       "      <td> 237.3</td>\n",
       "      <td> 243.39</td>\n",
       "      <td> 301.7</td>\n",
       "      <td> 44.03</td>\n",
       "      <td> 55.97</td>\n",
       "      <td> 185</td>\n",
       "      <td>  1</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monsters University</th>\n",
       "      <td> 2013</td>\n",
       "      <td> 107</td>\n",
       "      <td>  78</td>\n",
       "      <td> 74</td>\n",
       "      <td> 65</td>\n",
       "      <td>  82.43</td>\n",
       "      <td>  743.6</td>\n",
       "      <td> 268.5</td>\n",
       "      <td> 269.59</td>\n",
       "      <td> 475.1</td>\n",
       "      <td> 36.11</td>\n",
       "      <td> 63.89</td>\n",
       "      <td> 200</td>\n",
       "      <td>  0</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inside Out</th>\n",
       "      <td> 2015</td>\n",
       "      <td> 102</td>\n",
       "      <td>  98</td>\n",
       "      <td> 88</td>\n",
       "      <td> 93</td>\n",
       "      <td>  90.40</td>\n",
       "      <td>  677.1</td>\n",
       "      <td> 340.5</td>\n",
       "      <td> 340.50</td>\n",
       "      <td> 336.6</td>\n",
       "      <td> 50.29</td>\n",
       "      <td> 49.71</td>\n",
       "      <td> 175</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Year Released  Length  RT Score  IMDB Score  \\\n",
       "Movie                                                              \n",
       "Toy Story                     1995      81       100          83   \n",
       "A Bug's Life                  1998      96        92          72   \n",
       "Toy Story 2                   1999      92       100          79   \n",
       "Monsters, Inc.                2001      90        96          81   \n",
       "Finding Nemo                  2003     104        99          82   \n",
       "The Incredibles               2004     115        97          80   \n",
       "Cars                          2006     116        74          72   \n",
       "Ratatouille                   2007     111        96          80   \n",
       "WALL-E                        2008      97        96          84   \n",
       "Up                            2009      96        98          83   \n",
       "Toy Story 3                   2010     103        99          84   \n",
       "Cars 2                        2011     113        39          63   \n",
       "Brave                         2012     100        78          72   \n",
       "Monsters University           2013     107        78          74   \n",
       "Inside Out                    2015     102        98          88   \n",
       "\n",
       "                     Metacritic Score  Opening Weekend  Worldwide Gross  \\\n",
       "Movie                                                                     \n",
       "Toy Story                          92            29.14            362.0   \n",
       "A Bug's Life                       77            33.26            363.4   \n",
       "Toy Story 2                        88            57.39            485.0   \n",
       "Monsters, Inc.                     78            62.58            528.8   \n",
       "Finding Nemo                       90            70.25            895.6   \n",
       "The Incredibles                    90            70.47            631.4   \n",
       "Cars                               73            60.12            462.0   \n",
       "Ratatouille                        96            47.00            623.7   \n",
       "WALL-E                             94            63.10            521.3   \n",
       "Up                                 88            68.11            731.3   \n",
       "Toy Story 3                        92           110.31           1063.2   \n",
       "Cars 2                             57           109.00            559.9   \n",
       "Brave                              69            66.30            539.0   \n",
       "Monsters University                65            82.43            743.6   \n",
       "Inside Out                         93            90.40            677.1   \n",
       "\n",
       "                     Domestic Gross  Adjusted Domestic Gross  \\\n",
       "Movie                                                          \n",
       "Toy Story                     191.8                   356.21   \n",
       "A Bug's Life                  162.8                   277.18   \n",
       "Toy Story 2                   245.9                   388.43   \n",
       "Monsters, Inc.                255.9                   366.12   \n",
       "Finding Nemo                  339.7                   457.46   \n",
       "The Incredibles               261.4                   341.28   \n",
       "Cars                          244.1                   302.59   \n",
       "Ratatouille                   206.4                   243.65   \n",
       "WALL-E                        223.8                   253.11   \n",
       "Up                            293.0                   318.90   \n",
       "Toy Story 3                   415.0                   423.88   \n",
       "Cars 2                        191.5                   194.43   \n",
       "Brave                         237.3                   243.39   \n",
       "Monsters University           268.5                   269.59   \n",
       "Inside Out                    340.5                   340.50   \n",
       "\n",
       "                     International Gross  Domestic %  International %  \\\n",
       "Movie                                                                   \n",
       "Toy Story                          170.2       52.98            47.02   \n",
       "A Bug's Life                       200.6       44.80            55.20   \n",
       "Toy Story 2                        239.2       50.70            49.32   \n",
       "Monsters, Inc.                     272.9       48.39            51.61   \n",
       "Finding Nemo                       555.9       37.93            62.07   \n",
       "The Incredibles                    370.0       41.40            58.60   \n",
       "Cars                               217.9       52.84            47.16   \n",
       "Ratatouille                        417.3       33.09            66.91   \n",
       "WALL-E                             297.5       42.93            57.07   \n",
       "Up                                 438.3       40.07            59.93   \n",
       "Toy Story 3                        648.2       39.03            60.97   \n",
       "Cars 2                             368.4       34.20            65.80   \n",
       "Brave                              301.7       44.03            55.97   \n",
       "Monsters University                475.1       36.11            63.89   \n",
       "Inside Out                         336.6       50.29            49.71   \n",
       "\n",
       "                     Production Budget  Oscars Nominated  Oscars Won  \n",
       "Movie                                                                 \n",
       "Toy Story                           30                 3           0  \n",
       "A Bug's Life                        45                 1           0  \n",
       "Toy Story 2                         90                 1           0  \n",
       "Monsters, Inc.                     115                 3           1  \n",
       "Finding Nemo                        94                 4           1  \n",
       "The Incredibles                     92                 4           2  \n",
       "Cars                                70                 2           0  \n",
       "Ratatouille                        150                 5           1  \n",
       "WALL-E                             180                 6           1  \n",
       "Up                                 175                 5           2  \n",
       "Toy Story 3                        200                 5           2  \n",
       "Cars 2                             200                 0           0  \n",
       "Brave                              185                 1           1  \n",
       "Monsters University                200                 0           0  \n",
       "Inside Out                         175               NaN         NaN  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pixar_movies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Visualization, Line Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10eca6550>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NbZ07uT97ea4FQYD95f53HPulVlRmK2q05Mfk+v34CieFgL4CuZKumojJtBvg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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e908780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "critics_reviews = pixar_movies[[\"RT Score\",\"Metacritic Score\",\"IMDB Score\"]]\n",
    "critics_reviews.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10eb36630>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lwELgTqPRmAw8C+wxmUxpwN6hn8fk7nm3oVKo+KBsF4OzJOUvELiCkZluc6Bc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\nc8O7AKxdGpmd2LJj9Fm3Do+PnZUd2PLbAFgdwzJpz8cf0XD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xYNlhKNZknJXdfNS6h3U5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XAAAg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ed1f198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "critics_reviews.plot(figsize=(10,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Visualization, Box Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10f734828>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f748358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pixar_movies[[\"RT Score\",\"Metacritic Score\",\"IMDB Score\"]].plot(kind=\"box\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10f5a7cf8>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f922828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pixar_movies[[\"RT Score\",\"Metacritic Score\",\"IMDB Score\"]].plot(kind=\"box\", figsize=(9,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Visualization, Stacked Bar Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10e9cd080>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vX69mPUf1VE/1Wl+vPf9uqpdGPWhZWE0B5mZf12VtjDezHdz9cWAIMLapBurqZjTe8JRp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\n+3/dIAwJEuMWcQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e9c42b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "revenue_proportions = filtered_pixar[[\"Domestic %\", \"International %\"]]\n",
    "revenue_proportions.plot(kind='bar', stacked=True, figsize=(7,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Next Steps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10f26c400>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fxImdy01znkGSJD0rjR49eoU9i/Ts5hgkSZKkCgOSJElShQFJkiSpwoAkSZJUYUCSJEmq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f56d0b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grouped bar plot for oscar nominations / oscars won\n",
    "filtered_pixar[[\"Oscars Nominated\",\"Oscars Won\"]].plot(kind='bar', figsize=(10,6))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}